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All Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Audiansyah Agni Nirvana
Unknown Affiliation
Automotive Engineering Computer Science & IT Control & Systems Engineering

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Analysis of Fatigue Levels Using Multiple Linear Regression Methods on PT XYZ Workers Audiansyah Agni Nirvana; Rizqi Novita Sari
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.774

Abstract

PT XYZ is a company engaged in warehousing. In every process, there are various activities that can cause fatigue in workers. Currently, researchers want to analyze the effect of body condition, material, and warehouse conditions on the fatigue level of warehouse workers. To do this, companies can use multiple linear regression tests with SPSS software. In the multiple linear regression test that has been carried out, it is known that the body condition and material factors do not have a strong influence on the level of fatigue that occurs. This is because the Pvalue >0.05. While the warehouse condition factor has a strong influence on the level of fatigue, H0 is rejected because it has a Pvalue of 0.015 <0.05. From the results of the anova test conducted, it can be seen that the three existing factors simultaneously affect the fatigue level of PT XYZ workers. This is because the significance value in the anova test is 0.004; smaller than the value of 0.005. The benefit of this research is that PT XYZ can determine the right solution in order to reduce the level of fatigue so that warehouse productivity increases.
Co-Authors Rizqi Novita Sari